A prediction modeling based on SNOT-22 score for endoscopic nasal septoplasty: a retrospective study
| Autor: | Yi-Sheng Chen, Xue-Ran Kang, Runjie Shi, Bin Yi, Shulun Wang, Lixing Lu, Bin Chen, Chenyan Jiang, Xiaojun Yan |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Quality of life
medicine.medical_specialty medicine.medical_treatment Surgery and Surgical Specialties lcsh:Medicine Logistic regression General Biochemistry Genetics and Molecular Biology 03 medical and health sciences 0302 clinical medicine medicine Nasal septum Nasal septum deviation (NSD) 030223 otorhinolaryngology Sinusitis Septoplasty business.industry General Neuroscience lcsh:R SNOT-22 score Retrospective cohort study General Medicine Nomogram medicine.disease Surgery medicine.anatomical_structure Otorhinolaryngology 030220 oncology & carcinogenesis Nomogram prediction model Predictive power Public Health General Agricultural and Biological Sciences business |
| Zdroj: | PeerJ, Vol 8, p e9890 (2020) PeerJ |
| ISSN: | 2167-8359 |
| Popis: | Background To create a nomogram prediction model for the efficacy of endoscopic nasal septoplasty, and the likelihood of patient benefiting from the operation. Methods A retrospective analysis of 155 patients with nasal septum deviation (NSD) was performed to develop a predictive model for the efficacy of endoscopic nasal septoplasty. Quality of life (QoL) data was collected before and after surgery using Sinonasal Outcome Test-22 (SNOT-22) scores to evaluate the surgical outcome. An effective surgical outcome was defined as a SNOT-22 score change ≥ 9 points after surgery. Multivariate logistic regression analysis was then used to establish a predictive model for the NSD treatment. The predictive quality and clinical utility of the predictive model were assessed by C-index, calibration plots, and decision curve analysis. Results The identified risk factors for inclusion in the predictive model were included. The model had a good predictive power, with a AUC of 0.920 in the training group and a C index of 0.911 in the overall sample. Decision curve analysis revealed that the prediction model had a good clinical applicability. Conclusions Our prediction model is efficient in predicting the efficacy of endoscopic surgery for NSD through evaluation of factors including: history of nasal surgery, preoperative SNOT-22 score, sinusitis, middle turbinate plasty, BMI, smoking, follow-up time, seasonal allergies, and advanced age. Therefore, it can be cost-effective for individualized preoperative assessment. |
| Databáze: | OpenAIRE |
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